def post(self):
"""
Given a list of subjects id, returns related entities
"""
es = current_app.extensions['esquery']
parser = boilerplate.get_parser()
parser.add_argument('subject',
type=str,
action='append',
required=False,
help="subjects to get relations for")
parser.add_argument('object',
type=str,
action='append',
required=False,
help="objeects to get relations for")
parser.add_argument('sort',
type=str,
required=False,
action='append',
help="sort the results by this score type",
default=['scores.overlap'])
args = parser.parse_args()
subjects = args.pop('subject', []) or []
objects = args.pop('object', []) or []
res = es.get_relations(subjects, objects, **args)
if not res:
abort(404,
message='Cannot find relations for id %s' % str(subjects))
return CTTVResponse.OK(res)
def get(self):
"""
Given a list of target ids returns target generic information
"""
es = current_app.extensions['esquery']
parser = boilerplate.get_parser()
parser.add_argument('id',
type=str,
required=False,
action='append',
help="target ids to get the information")
parser.add_argument('fields',
type=str,
required=False,
action='append',
help="fields to include in the output")
kwargs = parser.parse_args()
target_ids = kwargs.pop('id', []) or []
res = es.get_gene_info(target_ids, **kwargs)
if res:
return CTTVResponse.OK(res)
abort(404, message="Gene id %s cannot be found" % target_ids)
class FreeTextSearch(Resource, Paginable):
parser = boilerplate.get_parser()
parser.add_argument('q', type=str, required=True, help="Query cannot be blank")
parser.add_argument('filter', type=str, required=False, action='append', help="filter by target or disease")
parser.add_argument('highlight', type=boolean, required=False,
help="return where the query was matched, defaults to true")
parser.add_argument('fields', type=str, action='append', required=False,
help="specify the fields to return for each object")
parser.add_argument('search_profile', type=str, required=False,
help="specify the entity type to look for. Only {drug|all} at the momment")
def get(self):
"""
Search for gene and disease
Search with a parameter q = 'your query'
"""
start_time = time.time()
kwargs = self.parser.parse_args()
searchphrase = kwargs.pop('q')
filter = kwargs.pop('filter')
if len(searchphrase) > 1:
res = current_app.extensions['esquery'].free_text_search(searchphrase,
doc_filter=filter, **kwargs)
return CTTVResponse.OK(res, took=time.time() - start_time)
else:
abort(400, message="Query is too short")
def post(self):
"""
Given a list of subjects id, returns related entities
"""
es = current_app.extensions['esquery']
parser = boilerplate.get_parser()
parser.add_argument('dataset',
type=str,
required=True,
help="name of the dataset")
parser.add_argument('query',
type=str,
required=True,
help="query to retrieve data in ES format")
args = parser.parse_args()
dataset_name = args.get('dataset', '')
print("post ", dataset_name)
es_query = args.get('query', '')
if not es_query:
abort(404, message='No query specified in the request')
res = es.get_documents_from_dataset(dataset_name, es_query)
if not res:
abort(404,
message='Cannot find relations for id %s' % str(subjects))
return CTTVResponse.OK(res)
def get(self):
"""
Given a dataset name and an ES query, returns all documents from this dataset
"""
es = current_app.extensions['esquery']
parser = boilerplate.get_parser()
parser.add_argument('dataset',
type=str,
required=True,
help="name of the dataset")
parser.add_argument('query',
type=str,
required=True,
help="query to retrieve data in ES format")
args = parser.parse_args()
dataset_name = args.get('dataset', '')
print("get ", dataset_name)
es_query = args.get('query', '')
if not es_query:
abort(404, message='No query specified in the request')
res = es.get_documents_from_dataset(dataset_name, es_query)
if not res:
abort(404,
message='Cannot find documents for dataset %s' %
str(dataset_name))
return CTTVResponse.OK(res)
class BestHitSearch(restful.Resource, Paginable):
'''This is similar to freeTextSearch but different because it allows for a list of search queries instead of one
query'''
parser = boilerplate.get_parser()
parser.add_argument('q',
type=str,
action='append',
required=True,
help="Query cannot be blank")
parser.add_argument('filter',
type=str,
required=False,
action='append',
help="filter by target or disease")
parser.add_argument(
'highlight',
type=boolean,
required=False,
help="return where the query was matched, defaults to true")
@is_authenticated
@rate_limit
def get(self):
"""
Search for gene and disease
Search with a parameter q = 'your query'
'fields':['id', 'approved_symbol']
"""
start_time = time.time()
kwargs = self.parser.parse_args()
filter_ = kwargs.pop('filter') or ['all']
searchphrases = kwargs.pop('q')
if len(searchphrases) > 500:
raise AttributeError('request size too big')
res = current_app.extensions['esquery'].best_hit_search(
searchphrases, doc_filter=filter_, **kwargs)
return CTTVResponse.OK(res, took=time.time() - start_time)
@is_authenticated
@rate_limit
def post(self):
"""
Search for gene and disease
Search with a parameter q = 'your query'
"""
start_time = time.time()
kwargs = request.get_json(force=True)
filter_ = [kwargs.pop('filter')] or ['all']
searchphrases = kwargs.pop('q')
if len(searchphrases) > 500:
raise AttributeError('request size too big')
res = current_app.extensions['esquery'].best_hit_search(
searchphrases, doc_filter=filter_, **kwargs)
return CTTVResponse.OK(res, took=time.time() - start_time)
def get(self, target_id):
"""
Given a target id, returns related targets
"""
es = current_app.extensions['esquery']
parser = boilerplate.get_parser()
parser.add_argument('sort', type=str, required=False, action='append',
help="sort the results by this score type", default=['scores.overlap'])
args = parser.parse_args()
res = es.get_relations([target_id],[], **args)
if not res:
abort(404, message='Cannot find relations for id %s'%str(target_id))
return CTTVResponse.OK(res)
def get(self):
"""
Get association objects
Get association objects for a gene, an efo or a combination of them
Test with ENSG00000136997
"""
parser = boilerplate.get_parser()
parser.add_argument('target', type=str, action='append', required=False,)
# parser.add_argument('gene-bool', type=str, action='store', required=False, help="Boolean operator to combine genes")
parser.add_argument('disease', type=str, action='append', required=False, )
# parser.add_argument('efo-bool', type=str, action='store', required=False, help="Boolean operator to combine genes")
parser.add_argument('therapeutic_area', type=str, action='append', required=False, )
parser.add_argument('scorevalue_min', type=float, required=False, )
parser.add_argument('scorevalue_max', type=float, required=False, )
parser.add_argument('scorevalue_types', type=str, required=False, action='append',)
parser.add_argument('datasource', type=str, action='append', required=False,)
parser.add_argument('datatype', type=str, action='append', required=False, )
parser.add_argument('pathway', type=str, action='append', required=False, )
parser.add_argument(FilterTypes.TARGET_CLASS, type=int, action='append', )
parser.add_argument('uniprotkw', type=str, action='append', required=False,)
parser.add_argument('rna_expression_level', type=int, default=0,
choices=list(xrange(0, 11)), required=False)
parser.add_argument('rna_expression_tissue', type=str, action='append',
required=False, default=[])
parser.add_argument('protein_expression_level', type=int, default=0,
choices=list(xrange(0, 4)), required=False)
parser.add_argument('protein_expression_tissue', type=str, action='append',
required=False, default=[])
parser.add_argument('go', type=str, action='append', required=False,
help="consider only genes linked to this GO term")
# parser.add_argument('filter', type=str, required=False, help="pass a string uncluding the list of filters you want to apply in the right order. Only use if you cannot preserve the order of the arguments in the get request")
# parser.add_argument('outputstructure', type=str, required=False, help="Return the output in a list with 'flat' or in a hierarchy with 'tree' (only works when searching for gene)", choices=['flat','tree'])
parser.add_argument('targets_enrichment', type=str, required=False, help="disease enrichment analysis for a set of targets")
parser.add_argument('direct', type=boolean, required=False,)
parser.add_argument('facets', type=str, required=False, default="")
parser.add_argument('facets_size', type=int, required=False, default=0)
parser.add_argument('sort', type=str, required=False, action='append',)
parser.add_argument('search', type=str, required=False, )
parser.add_argument('cap_scores', type=boolean, required=False, )
args = parser.parse_args()
self.remove_empty_params(args)
data = self.get_association(params=args)
return CTTVResponse.OK(data)
def get(self):
"""
Get a list of evidences filtered by gene, efo and/or eco codes
test with: ENSG00000136997,
"""
parser = boilerplate.get_parser()
parser.add_argument('target',
type=str,
action='append',
required=False,
help="ensembl id in target.id")
# parser.add_argument('gene-bool', type=str, action='store', required=False, help="Boolean operator to combine genes")
parser.add_argument('disease',
type=str,
action='append',
required=False,
help="List of efo code in disease")
# parser.add_argument('efo-bool', type=str, action='store', required=False, help="Boolean operator to combine genes")
parser.add_argument('eco',
type=str,
action='append',
required=False,
help="List of evidence types as eco code")
# parser.add_argument('eco-bool', type=str, action='store', required=False, help="Boolean operator to combine evidence types")
# parser.add_argument('body', type=str, action='store', required=False, location='form', help="json object with query parameter")
parser.add_argument('datasource',
type=str,
action='append',
required=False,
help="List of datasource to consider")
parser.add_argument('datatype',
type=str,
action='append',
required=False,
help="List of datatype to consider")
# parser.add_argument('auth_token', type=str, required=True, help="auth_token is required")
# parser.add_argument('direct', type=boolean, required=False, help="return only evidence directly associated with the efo term if false or to all its children if true", default=False)
parser.add_argument('pathway',
type=str,
action='append',
required=False,
help="pathway involving a set of genes")
parser.add_argument('uniprotkw',
type=str,
action='append',
required=False,
help="uniprot keyword linked to a set of genes")
parser.add_argument('scorevalue_min',
type=float,
required=False,
help="filter by minimum score value")
parser.add_argument('scorevalue_max',
type=float,
required=False,
help="filter by maximum score value")
parser.add_argument(
'sort',
type=str,
action='append',
required=False,
help=
"order the results by the given list of fields. default is score.association_score"
)
parser.add_argument('begin',
type=long,
required=False,
help="filter by range with this start")
parser.add_argument('end',
type=long,
required=False,
help="filter by range with this end")
parser.add_argument(
'chromosome',
type=str,
required=False,
help="filter by range required chromosome location")
args = parser.parse_args()
targets = args.pop('target', []) or []
# gene_operator = args.pop('gene-bool','OR') or 'OR'
diseases = args.pop('disease', []) or []
# object_operator = args.pop('efo-bool','OR') or 'OR'
evidence_types = args.pop('eco', []) or []
# evidence_type_operator = args.pop('eco-bool','OR') or 'OR'
datasources = args.pop('datasource', []) or []
datatypes = args.pop('datatype', []) or []
if args.get('sort') is None:
args['sort'] = [EvidenceSortOptions.SCORE]
# if not (genes
# or objects
# or evidence_types
# or datasources
# or datatypes
# or args['pathway']
# or args['uniprotkw']
# or args['datatype']):
# abort(404, message='Please provide at least one gene, efo, eco or datasource')
data = self.get_evidence(targets,
diseases,
evidence_types,
datasources,
datatypes,
params=args)
return CTTVResponse.OK(data, )
